1. Bicyclist Health and Safety Issues on Four Alternative Transportation Routes Monroe County Alternative Transportation Plan Risk Assessment Craig Harper · ZeynepAltinay Courtney Bonney ·Max Jie Cui
7. Target population Current study: Adult male 18-30 years old 70 kg weight Cycling at a moderate pace (13 mph) Asthmatic adult male Future Studies: Adult female Elderly Children
8. Hazard ID Criteria Pollutants Sulfur Dioxide Nitrogen Oxides Particulate matter < 2.5 µm Hazardous Air Pollutants VOCs (e.g. Benzene)
9. Bicyclists’ Health and Safety: A Conceptual Site Model Bicyclists share roads with vehicles Road Characteristics (type, lane width, shoulder, sidewalk, signage, bike lanes, etc) Pollutants emitted from vehicles Function of: fleet makeup, traffic volume, fuel composition, season Driver and Bicyclists Error Dispersal of Pollutants Function of: wind velocity, mixing height, season, buffer width Accident Rate Traffic and Bicycle Volume (vary spatially and temporally) Inhalation of Pollutants Function of: inhalation rate (varies with population) Confounding Factors Weather, distractions Pollutant Dose Function of: absorption Endpoints: Predicted number of accidents on a given route (accidents/year) Health Response (acute or chronic) Endpoints: Risk to bicyclists from particular pollutants (mg/kg/day) over the course of 30 years
11. Route 1State Road 46 Commuter Route with a possible greenway option that would encourage recreational users Vehicle Traffic Volume: Current: 10704-19071 Avg: 15000 Alternative 1: 10700 Alternative 2: 4900-13000
12. Route 2State Road 45 Recreational Route from Lake Lemon into Bloomington Vehicle Traffic Volume: Current: 3422-11491 Avg: 5225 Typical Multiuse Volumes:
13. Route 33rd to Ivy Tech Commuter Route to Ivy Tech Vehicle Traffic Volume: Current: 102 – 42803 Avg: 17100 Alternative 1: Alternative 2:
14. Route 4Fairfax Rd Recreational Route from Clear Creek Trail head to Monroe Lake Beach and Four Winds Resort Volume: Current: 49-6860 Avg: 2270
17. Exposure: Methods EPA ‘s Mobile 6.2 Emissions Modeling Software Estimates emissions (g/s or g/day) Assumes average fleet makeup, traffic volumes, seasonal variations, fuel composition, average speed http://elseware.univ-pau.fr/MAINPAGEPUB/carpollu/pol1.gif
18. Dispersion Box Model Concentration (C) Where , The emission rate per unit area Assumptions of the box model: Concentrations are homogenous within the box. Sources distribute uniformly. Emitted pollutants instantaneously and uniformly mix. A wind of constant speed flows across the cells cross-sectional area (Schnelle and Dey, 2000)
19. Calculation of Intakes Where: I ≡ intake (mg/kg bodyweight/day) C ≡ chemical concentration (mg/s) CR ≡ contact rate (m3/hr) EFD ≡ exposure frequency and duration EFD = EF*ED EF ≡ exposure frequency (days/year) ED ≡ exposure duration (years) BW ≡ bodyweight; the average bodyweight over the exposure period (kg) AT ≡ averaging time; time over which exposure is averaged (days)
20. Combined Health Effects Respiratory Inflammation Reduced Lung Function (FEV1/FVC) Increased Upper Respiratory Infections Bronchitis Pneumonia Allergic Reactions Exacerbation of COPD, Asthma, and Emphysema Central Nervous System Headaches/Dizziness/Vomiting Brain damage asphyxiation Stroke Coma (VOCs) Cardiovascular Increased myocardial ischemia Pro-inflammatory mediators Atherosclerosis Leukocyte and platelet activation Arrhythmia Increased risk of diabetes and hypertension Cancer Lung Cancer Leukemia Premature Death
22. Cancer VOCs (Benzene as an example) and PM have the ability to cause cancer Risk measured as Unit Risk: risk per µg/m3 breathed Benzene – Leukemia (EPA, 1998) Unit Risk = 7.8E-03 (mg/m3)-1 Slope Factor = 2.73E-02 (mg/kg-day)
23. Modeling Uncertainties Calculated RfC from threshold doses corrected for uncertainty (see table) Utilized @Risk to run 5000 iterations 5 frequency durations ranging from 50-250 days Used @Risk to place uncertainty values around: wind speed mixing height width of box
24. Non-Cancer Output from @risk Calculated a HQ with nested uncertainties for the longest route in 4 seasons NOx: HQ>1 All other pollutants HQ<1 Relative Hazard Index, sum of the HQs, calculated for varying proposed alternatives
27. Data gaps/uncertainty Mobile 6.2 default traffic volume assumption no account of road dust exposure from ingestion mixing height assumptions interactive effects of pollutants
31. Assumption: Bicycle/pedestrian volume Months of Cycling Michael Steinhoff and Julie Harpring. (2008). Transportation and Sustainability on the Indiana University, Bloomington Campus.
33. Model Type I – Bicycle Y = − 0.00308 + 0.70576abm – 0.00513aps – 0.25012week + 0.00014143B2 + ut R2= 16.36% F=17.5 P=0.0001 Y = Number of accident(s) on each day of 2008 abm = Hourly Bike flow adjusted by month; t=7.07 aps = Hourly pedestrian flow adjusted by season; t=5.5 week = (Weekend=1, weekday=0); t=4.4 B2=Abm2 ; t=0.88
34. Model Type II Y = 0.61697 +0.00005965TF +0.06912LW2 +0.19403BLW -0.84127Int -0.28712Curb -0.21508SD+ 0.34976 CR R2=96.63% F =36.81 P=0.0001 Y = # of Accidents on each selected road in 2008 TF = Average Traffic Flow per day (2008) t=7.39 LW = Lane Width t=24.99 BLW = Bike Lane Width t=3.87 Intersection (INT) = (Yes=1, No=0) t=-3.55 Curb (CB) = (Yes=1, No=0) t=1.88 Sidewalk (SD) = (Yes=1, No=0) t=1.45 CR = (Commercial =1,Residential=0) t=2.27
35. Limitations Cannot account for human behavior Mixed-Poisson Distribution Model Data is very limited in this area. Specification Error
36. Next steps to improve accident modeling Collect more data of risk characteristics on our primary routes (accidents!) Adjust the model by adopting Mixed Poisson Distribution and take human behavior into consideration Improve the assumptions by getting more official data
37. Conclusions Little evidence of serious risk due to air pollutants on current routes Cannot make predictions of accidents on rural routes based on our model Cannot make generalizations about effects of multi-use path with our model Traffic calming measures (reduction of volume) seems to be more effective at reducing accidents than adding bike lanes
38. Further Considerations Value of increasing perceived safety Produce a map of county bike routes with safety rating based on road characteristics to inform bicyclists of options
Editor's Notes
Title Slide:
OutlineAssume 8th Grade Education
State Road 45 put in our GIS routes with hotspots
State Road 45 put in our GIS routes with hotspots
State Road 45 put in our GIS routes with hotspots
State Road 45 put in our GIS routes with hotspots
State Road 46
CardiovascularIncreased myocardial ischemiaPro-inflammatory mediatorsAtherosclerosisLeukocyte and platelet activationArrhythmiaIncreased risk of diabetes and hypertensionIncreased levels of CRPIncreased coagulabilityAltered rheologyCancerLung CancerLeukemiaPremature Death
Road CharacteristicsLane Width, Bike Lane, etc.Traffic and Bicycle VolumeMotor Vehicle Volume, Ped Volume, and Cyclist VolumeConfounding FactorsWeather, Commercial/Residential, Daily Changes in BehaviorDriver and Bicyclist ErrorFaulty bicycle mechanists